Process Production Operations

Empowering production operations in process industries to shorten time to market and maximize profitability by leveraging process and quality data

BIOVIA InVision Data Analytics Capabilities

Statistical Capabilities

Basic and advanced univariate and multivariate statistical tools help scientists easily access and analyze everyday process data. For example, scientists can use Two-Sample t-tests to compare the average of two groups to find out if they are significantly different.

Statistical Examples:
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Principal Component Analysis (PCA)
Principal Component Analysis (PCA) can be used to transform a large data set with a large number of correlated variables into a smaller set of uncorrelated variables. These variables can be used in other types of analyses carried out both inside and outside the BIOVIA Discoverant application.


Plotting Capabilities

Scientists can compare data graphically by plotting a wide range of parameters displayed across multiple panels to analyze a single batch, multiple batches, or groups of batches. Summarization functions are enhanced to assist scientists in understanding the historical data. An easy point-and-click function allows scientists to overlay the progress of the current batch in real-time onto historical batches to assess performance against the "golden batch."

Plotting Examples:

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Quality Monitoring

Quality Monitoring provides Statistical Process Control (SPC) for real-time process monitoring and automated alerts. Using a variety of control charts, scientists can plot and monitor a process visually against pre-determined limits. Process Capability functionality allows scientists to set multiple limits and see the predicted failure rates based on actual process performance.


Stability and Expiration Dating (SED)

Plotting and linear regression modeling capabilities allow you to inspect and analyze stability study data in a flexible manner to calculate expiration estimates that conform to existing industry standards. Alternate linear regression modeling strategies can be used to pool production lots and obtain a more reduced model when it is appropriate to do so. Scientists can also use the Stability Out-of-Trend (OOT) alerting capabilities that allow detecting out-of-trend study results while stability studies are in progress. Different evaluation methods give you the ability to analyze stability parameter trends, either within batches or by comparison with trend estimates generated from a combined set of historical study results contained in a designated reference data set.

Stability Studies and Expiration Dating Examples:

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Curve Metrics®

Curve Metrics® provides scientists with point-and-click tools needed to work comprehensively with continuous data and extract features on screen. Scientists can combine quantified features with other discrete and replicate data for analysis. With Advanced Profile Analysis (APA), scientists can analyze multiple time series parameters simultaneously to determine which of them in combination (and when) are the best predictors of the process outcome.

Curve Metrics Examples:

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Visual Process Signatures® (VPS)

Visual Process Signatures® (VPS) provides animated visualizations of interactions among process parameters over time, or in relation to the value of a selected process parameter or process outcome. VPS can uncover otherwise hidden parameter relationships in the manufacturing process and identify parameters that warrant further analysis to improve process control.

Visual Process Signatures Examples:



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Multi-Phase Analysis (MPA)

Multi-Phase Analysis (MPA) provides enhanced ways to examine chromatography, fermentation and other multi-phase data. MPA enables automatic or point-and-click identification of the phases in continuous data. Once identified, phases can be visually and quantitatively compared individually or in groups. MPA can be used to more accurately determine the useful life of costly chromatography resins to avoid premature, or late, replacement, thereby minimizing the risk of impurities entering the product stream.

Multi-Phase Analysis Examples:

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